A consensus model based on rough bipolar fuzzy approximations

2019 ◽  
Vol 36 (4) ◽  
pp. 3461-3470 ◽  
Author(s):  
Nosheen Malik ◽  
Muhammad Shabir
Keyword(s):  
2021 ◽  
Vol 70 ◽  
pp. 12-26
Author(s):  
Weiwei Guo ◽  
Zaiwu Gong ◽  
Xiaoxia Xu ◽  
Ondrej Krejcar ◽  
Enrique Herrera-Viedma

2021 ◽  
Author(s):  
Francisco Javier Cabrerizo ◽  
José Ramón Trillo ◽  
Juan Antonio Morente-Molinera ◽  
Sergio Alonso ◽  
Enrique Herrera-Viedma

2018 ◽  
Vol 18 (3) ◽  
Author(s):  
Carlos Henrique Franciscon ◽  
Izildinha de Souza Miranda

Abstract: This study conducts a biogeographical review of Aniba in Brazil, including its actual and potential distribution, and a review on the species conservation status. The potential distribution of each Aniba species was modeled using the Brazilian Plants and Fungi Biogeography system, which is interconnected with the SpeciesLink network. A consensus model based on up to five algorithms was used to model the potential distribution of each species. The endemism, conservation status and rarity of each species in Brazil were also analyzed. A total of 3059 records of 30 Brazilian Aniba species were found. In total, 16.1% of the records were excluded because of the lack of valid names, and 53.4% were excluded because of the lack of georeference and name of the person who identified the record. The consensus model showed good results for species with 20 or more pixels. The other species had many errors, and their models could only be used to determine new areas for collections. Nine species were endemic to Brazil, and only three species showed no indicator of rarity. The geographical distribution of Brazilian Aniba species shows a predominantly Amazonian pattern. Only four species are not actually found in the Amazon. Some Amazonian species may also be found in Atlantic Forest areas, and many other species have the potential to live there. Our results indicate that only three species have no conservation problems, whereas 14 species have conservation problems, and 13 other species require further population studies to be best evaluated.


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